Ongoing discussions on perceptual averaging have the implicit assumption that individual representations are reduced into a single prototypical representation. However, some evidence suggests that the mean representation may be more complex. For example, studies that use a single item probe to estimate mean size often show biased estimations. To this end, we investigate whether the mean representation of size is reduced to a single mean or includes other properties of the set. Participants estimate the mean size of multiple circles in the display set by adjusting the mean size of the circles in the probe set that followed. Across 3 experiments, we vary the similarity of set-size, variance, and skewness between the display and probe sets and examine how property congruence affects mean estimation. Altogether, we find that keeping properties consistent between the 2 compared sets improves mean estimation accuracy. These results suggest that mean representation is not simply encoded as a single mean but includes properties such as numerosity, variance, and the shape of a distribution. Such multiplex nature of summary representation could be accounted for by a population summary that captures the distributional properties of a set rather than a single summary statistic. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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